2.3k citations · 3.7k across the 45 of their papers we have counts for
5 papers · 1 filter
Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes
Simran Arora, Brandon Yang, Sabri Eyuboglu +4
A long standing goal of the data management community is to develop general, automated systems that ingest semi-structured documents and output queryable tables without human effor…
Ask Me Anything: A simple strategy for prompting language models
Simran Arora, Avanika Narayan, Mayee F. Chen +6
Large language models (LLMs) transfer well to new tasks out-of-the-box simply given a natural language prompt that demonstrates how to perform the task and no additional training.…
Metadata Shaping: Natural Language Annotations for the Tail
Simran Arora, Sen Wu, Enci Liu +1
Language models (LMs) have made remarkable progress, but still struggle to generalize beyond the training data to rare linguistic patterns. Since rare entities and facts are preval…
Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
Laurel Orr, Megan Leszczynski, Simran Arora +4
A challenge for named entity disambiguation (NED), the task of mapping textual mentions to entities in a knowledge base, is how to disambiguate entities that appear rarely in the t…
Contextual Embeddings: When Are They Worth It?
Simran Arora, Avner May, Jian Zhang +1
We study the settings for which deep contextual embeddings (e.g., BERT) give large improvements in performance relative to classic pretrained embeddings (e.g., GloVe), and an even…